Evidence map›Paper›PMID 41278787›Full record

ArticlebioRxiv : the preprint server for biology2025

Brain Entropy: Linking Brain Structure to Task Activation.

Donghui Song

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Donghui SongState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing,100091, China.ORCID 0000-0003-3722-0413

Funding

Mapping the Human Connectome: Structure, Function, and HeritabilityU54MH091657 · NIMH · WASHINGTON UNIVERSITY · PI UGURBIL, KAMIL, VAN ESSEN, DAVID C · 2010 to 2014
$34.7M
NIMH NIH HHS U54 MH091657
6 · The paper itself

Abstract

Understanding how the brain's complex and diverse functions emerge from its structure has long been a central goal of neuroscience. Entropy, a measure of system irregularity, has become a powerful tool for quantifying the dynamics of brain activity. While previous fMRI-based brain entropy (BEN) studies have established its relationships with brain morphology (e.g., gray matter volume, GMV) and task activation, the pathway from structure to function remains incompletely understood. Specifically, it is unclear whether controlling for brain morphology (GMV) significantly alters the observed BEN-task activation relationship. In this study, we first replicated key prior findings, including the effects of sex and age on BEN and GMV, their spatial and brain-wide voxel-wise correlations, and the relationship between BEN and task activation across social cognition, reward, and emotion tasks. Subsequently, we examined the correlation between GMV and task activation, as well as the correlation between BEN and task activation after controlling for GMV. Our results successfully replicated previous findings. Crucially, the relationship between BEN and task activation remained largely unchanged after controlling for GMV. This indicates that BEN captures unique variance in task activation beyond what is explained by GMV alone, establishing BEN as a functional bridge linking brain structure to task activation. Future work should employ predictive analyses to quantify the added value of BEN in predicting task activation from structural information.

Indexed as

Brain entropybrain structure and functionGray matter volumeMRITask activation

Identifiers

PMID41278787
PMCPMC12636292

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.